A self-tuning neurofuzzy integrating controller is derived in this paper for offset eliminating purpose. CARIMA plant model is used and the control law produces integral control terms in a natural way. Neurofuzzy networks are chosen to implement the direct self-tuning nonlinear integrating controller. The performance of the self-tuning integrating neurofuzzy controller is illustrated by example...

Human administration of storage systems is a large and growing issue in modern IT infrastructures. We are exploring new storage architectures that integrate automated management functions and simplify the human administrative task. Self-* storage systems (pronounced “self-star”— a play on the unix shell wild-card character) are self-configuring, self-organizing, self-tuning, self-healing, self-...

| This paper reports on results and experiences from the COMFORT automatic tuning project. The objective of the project has been to investigate architectural principles of self-tuning database and transaction processing systems, and to develop self-tuning methods for speciic performance tuning problems. A particular concern of the project has been to cope with workload dynamics and workload het...

In this paper, we developed the parametric estimation and the self-tuning control problem of the nonlinear systems which are described by discrete-time nonlinear mathematical models, with unknown, time-varying parameters, and operative in a stochastic environment. The parametric estimation is realized by using the prediction error method and the recursive least squares techniques. The self-tuni...

The handling of various input constraints in the self-tuning generalized predictive control (STGPC) problem of ARIMAX/ARMAX systems is considered. The methods based on the Lagrange multipliers and Lemke’s algorithm are used to solve the constrained optimization problem. A self-tuning controller is implemented in an indirect way, and the considered constraints imposed on the control input signal...

Currently, a considerable amount of human effort and time is spent for initialization or calibration of operational traffic control systems. Typically, this optimization (fine-tuning) procedure is conducted manually, via trial-and-error, relying on expertise and human judgment and does not always lead to a desirable outcome. This paper presents a new learning/adaptive algorithm that enables aut...

A model-based design and tuning procedure is proposed for feedforward controllers, which accounts for model uncertainties in SISO systems. Proper relationships for the analysis of feedforward–feedback control systems show that tuning the feedforward controller is not completely independent from the feedback-loop spectral characteristics. Similarly, fine tune of the associated feedback controlle...

The advances in MIMO systems and networking technologies introduced a revolution in recent times, especially in wireless and wired multi-cast (multi-point-to-multi-point) transmission field. In this work, the distributed versions of self-tuning proportional integral plus derivative (SPID) controller and self-tuning proportional plus integral (SPI) controller are described. An explicit rate feed...